Founding AI Engineer

About Kinro

Kinro builds AI sales agents for the insurance industry, automating the full sales flow from qualification and quoting to recommendations and binding. Our north star is selling insurance in LLM platforms (ChatGPT, Gemini….)

Launch video:
https://www.youtube.com/watch?v=z_bC6nejbbg

What you'll do

You will help define how Kinro builds software in the age of agents. This is a hands-on role for someone who has built AI products end-to-end, trusts agentic coding as a force multiplier, and can ship across product, backend, evals, and infrastructure with strong systems judgment.

• Build AI product systems end-to-end, from tool use and backend services to evals and production monitoring.
• Use agentic coding tools aggressively and responsibly: break down large problems, set guardrails, and review generated work with high standards.
• Improve agent quality, latency, safety, and cost through better architectures, feedback loops, and evaluation harnesses.
• Work across the stack wherever leverage is highest, including product surfaces, infra primitives, and customer deployments.
• Turn one-off lessons from production into reusable product and platform capabilities.

What we're looking for

• You have built AI products, agent workflows, or LLM systems end-to-end in production.
• You know when to trust an agent, when to intervene, and how to structure work so the agent succeeds.
• You understand tool calling, latency, reliability, security, and cost tradeoffs in agentic systems.
• You can reason across the stack: application code, APIs, databases, cloud systems, and operational tooling.
• You have strong product taste and care whether something feels simple, fast, and reliable for the end user.

Nice to have

• Experience with evals, model routing, prompt injection defenses, sandboxing, or other AI systems safety work.
• Experience in high-ownership product environments where engineers talk directly to users and ship quickly.
• Experience in fintech, insurance, or other regulated environments.

Interview Process

We aim to move quickly and keep the process practical.

1. Intro conversation (20–30 min)
A short call to understand your background, what you’ve built, and what you want next.

2. Technical / product deep dive (45–60 min)
We’ll talk through systems you’ve built end-to-end, including product decisions, architecture, tradeoffs, reliability, and how you shipped in production.

3. Founder / team conversations (45–60 min)
We’ll spend time on ownership, speed, taste, communication, and what it would look like to build together in person.

4. One week paid trial

You will join us on our day to day to on real topics to see how you fit.

5. References + final conversation
We’ll close quickly if there’s mutual fit.

We care most about people who can build useful products fast, reason clearly about tradeoffs, and raise the quality bar across the stack.